Infer.AI is a framework for quickly developing abstract interpretation-based checkers (intraprocedural or interprocedural). You define only:
- An abstract domain (type of abstract state plus
- Transfer functions (a transformer that takes an abstract state as input and produces an abstract state as output)
What you get in exchange is an analysis that can run on all of the languages Infer supports (C, Objective-C, C++, and Java)!
If you feel like coding instead of reading, a great way to get started with Infer.AI is to go through the lab exercise here.
By example: intraprocedural analysis
This section helps you get started ASAP if you already understand abstract interpretation (or don't, but are feeling bold).
Take a look at liveness.ml. This code is performing a compilers-101 style liveness analysis over SIL, Infer's intermediate language. Since this code is fairly small and you should already understand what it's trying to do, it's a fairly good place to look in order to understand both how to use the abstract interpretation framework and what SIL is.
There are basically three important bits here: defining the domain, defining the transfer functions, and then passing the pieces to the framework to create an an analysis. Let's break down the third bit:
ProcCfg.Backward (ProcCfg.Exceptional) part says: "I want the direction of
iteration to be backward" (since liveness is a backward analysis), and "I want
to the analysis to follow exceptional edges". For a forward analysis that
ignores exceptional edges, you would do
ProcCfg.Normal instead (and many other
combinations are possible; take a look at
for more). And finally, the
TransferFunctions part says "Use the transfer
functions I defined above".
Now you have a
CheckerAnalyzer module that exposes useful functions
(take a procedure as input and compute a postcondition) and
(take a procedure and compute an invariant map from node id's to the
pre/post at each node). The next step is to hook your checker up to
the Infer command-line interface (CLI). For the liveness analysis, you
would do this by exposing a function for running the checker on a
and then adding
Liveness.checker to the list of registered checkers
(search for "Liveness").
you can then run
infer run --liveness-only -- <your_build_command> to run your
checker on real code. See here for more
details on the build systems supported by Infer.
Useful analyses have output. Basic printing to stderr or stderr is
good for debugging, but to report a programmer-readable error that is
tied to a source code location, you'll want to use
By example: interprocedural analysis
Let's assume you have already read and understood the "intraprocedural analysis" section and have an intraprocedural checker. The abstract interpretation framework makes it easy to convert your intraprocedural analysis into a modular interprocedural analysis. Let me emphasize the modular point once more; global analyses cannot be expressed in this framework.
To make your checker interprocedural, you need to:
Define the type of procedure summaries for your analysis and let registerCheckers.ml know that your checker is interprocedural
Add logic for (a) using summaries in your transfer functions and (b) converting your intraprocedural abstract state to a summary.
A good example to look at here is Siof.ml. Step (1) is just:
Here, the type of the abstract state and the type of the summary are the same, which makes things easier for us (no logic to convert an abstract state to a summary).
Part (2a) is
and uses the
analyze_dependency callback provided by the framework:
This says: "read the summary for
callee_pname, possibly computing it
first". You must then add logic for applying the summary to the
current abstract state (often, this is as simple as doing a join).
Because our summary type is the same as the abstract state, part (2b)
here simply consists in return the post computed by the analysis as
the procedure's summary, using
That's it! We now have an interprocedural analysis.